GirardinValeriaGirard2022

Référence

Girardin, P., Valeria, O., Girard, F. (2022) Measuring Spatial and Temporal Gravelled Forest Road Degradation in the Boreal Forest. Remote Sensing, 14(3):457. (URL )

Résumé

Degradation of forest roads in Canada has strong negative effects on access to forestlands, together with economic (e.g., increased maintenance costs), environmental (e.g., erosion of materials and subsequent habitat contamination), and social (e.g., use risks) impacts. Maintaining sustainable and safe access to forestland requires a better understanding and knowledge of forest road degradation over time and space. Our study aimed to identify relevant spatiotemporal variables regarding the state of eastern Canadian forest road networks by (1) building predictive models of gravel forest road degradation and assessing effects of the slope, time, loss of the road surface, and road width (field approach), and (2) evaluating the potential of topography, roughness and vegetation indices obtained from Airborne Laser Scanning (ALS) data and Sentinel-2 optical images to estimate degradation rates (remote sensing approach). The field approach (n = 207 sample plots) confirmed that only four variables were efficient to estimate degradation rates (pseudo-R2 = 0.43 with ±8% error). Simulations that were conducted showed that after about five years without maintenance, the rate of degradation on a road, regardless of its width, increased exponentially, exacerbated by a high slope gradient and loss of road surface. The narrowest roads tended to degrade more rapidly over time. The remote sensing approach performed quite well (pseudo-R2 = 0.34 with ±9% error) in terms of predicting road degradation, giving us the valuable tools to spatialise the state of gravel forest road degradation in eastern Canadian forest. This study provided new knowledge and tools that are critical for maintaining and sustaining access to Canada’s boreal forest territory in both the short- and the long-term.

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@ARTICLE { GirardinValeriaGirard2022,
    AUTHOR = { Girardin, P. and Valeria, O. and Girard, F. },
    JOURNAL = { Remote Sensing },
    TITLE = { Measuring Spatial and Temporal Gravelled Forest Road Degradation in the Boreal Forest },
    YEAR = { 2022 },
    ISSN = { 2072-4292 },
    NUMBER = { 3 },
    PAGES = { 457 },
    VOLUME = { 14 },
    ABSTRACT = { Degradation of forest roads in Canada has strong negative effects on access to forestlands, together with economic (e.g., increased maintenance costs), environmental (e.g., erosion of materials and subsequent habitat contamination), and social (e.g., use risks) impacts. Maintaining sustainable and safe access to forestland requires a better understanding and knowledge of forest road degradation over time and space. Our study aimed to identify relevant spatiotemporal variables regarding the state of eastern Canadian forest road networks by (1) building predictive models of gravel forest road degradation and assessing effects of the slope, time, loss of the road surface, and road width (field approach), and (2) evaluating the potential of topography, roughness and vegetation indices obtained from Airborne Laser Scanning (ALS) data and Sentinel-2 optical images to estimate degradation rates (remote sensing approach). The field approach (n = 207 sample plots) confirmed that only four variables were efficient to estimate degradation rates (pseudo-R2 = 0.43 with ±8% error). Simulations that were conducted showed that after about five years without maintenance, the rate of degradation on a road, regardless of its width, increased exponentially, exacerbated by a high slope gradient and loss of road surface. The narrowest roads tended to degrade more rapidly over time. The remote sensing approach performed quite well (pseudo-R2 = 0.34 with ±9% error) in terms of predicting road degradation, giving us the valuable tools to spatialise the state of gravel forest road degradation in eastern Canadian forest. This study provided new knowledge and tools that are critical for maintaining and sustaining access to Canada’s boreal forest territory in both the short- and the long-term. },
    ARTICLE-NUMBER = { 457 },
    DOI = { 10.3390/rs14030457 },
    KEYWORDS = { access, airborne LiDAR, management, roughness, Sentinel-2, spatial indices, topography },
    OWNER = { Daniel Lesieur },
    TIMESTAMP = { 2022-01-19 },
    URL = { https://www.mdpi.com/2072-4292/14/3/457 },
}

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